Karen B Farris1, Teresa M Salgado2, Peter Batra2, John D Piette3, Satinder Singh4, Ahmed Guhad5, Sean Newman4, Vincent D Marshall2, Larry An6. 1. Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, USA. Electronic address: kfarris@umich.edu. 2. Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, USA. 3. Ann Arbor Department of Veterans Affairs Center for Clinical Management Research, Ann Arbor, USA; University of Michigan School of Public Health, Ann Arbor, USA; University of Michigan School of Medicine, Ann Arbor, USA. 4. Division of Computer Science and Engineering, Department of Electrical Engineering and Computer Science, University of Michigan College of Engineering, Ann Arbor, USA. 5. University of Michigan College of Pharmacy, Ann Arbor, USA. 6. Department of Internal Medicine, University of Michigan School of Medicine, Ann Arbor, USA.
Abstract
BACKGROUND: Text messages can improve medication adherence and outcomes in several conditions. For this study, experts developed text messages addressing determinants of medication adherence: disease beliefs, medication necessity, medication concerns, and forgetfulness, as well as positive reinforcement messages for patients who were adherent. OBJECTIVES: To validate expert-developed text messages to address medication non-adherence with a group of non-researchers. METHODS: A two-wave, card-sorting activity was conducted with students and staff at the University of Michigan. In the first wave, 40 participants grouped 32 messages addressing barriers for medication adherence (disease beliefs, medication necessity, medication concerns, and forgetfulness) according to their perceived relationship. Messages with poor grouping agreement were deleted or modified. In the second wave, positive reinforcement messages were developed and tested along with the previous categories (36 messages) by 37 participants. Similarity and cluster analyses were used to assess agreement between experts and participants. RESULTS: In the first card-sorting wave, participants grouped messages into between 2 and 13 separate categories. Similarity analysis showed four groupings of messages, however, some had an agreement below 50% and clusters appeared dispersed. In the second wave, and after messages being edited, participants grouped the messages into between 4 and 9 categories. Five groups (now including positive reinforcement messages) were identified with higher agreement in the similarity and cluster analyses. CONCLUSIONS: The structure of expert-developed text messages to address medication adherence key barriers was confirmed. Messages will be used in future research to determine their impact on affecting medication adherence to anti-hypertensive medications using a reinforcement learning controlled text messaging service.
BACKGROUND: Text messages can improve medication adherence and outcomes in several conditions. For this study, experts developed text messages addressing determinants of medication adherence: disease beliefs, medication necessity, medication concerns, and forgetfulness, as well as positive reinforcement messages for patients who were adherent. OBJECTIVES: To validate expert-developed text messages to address medication non-adherence with a group of non-researchers. METHODS: A two-wave, card-sorting activity was conducted with students and staff at the University of Michigan. In the first wave, 40 participants grouped 32 messages addressing barriers for medication adherence (disease beliefs, medication necessity, medication concerns, and forgetfulness) according to their perceived relationship. Messages with poor grouping agreement were deleted or modified. In the second wave, positive reinforcement messages were developed and tested along with the previous categories (36 messages) by 37 participants. Similarity and cluster analyses were used to assess agreement between experts and participants. RESULTS: In the first card-sorting wave, participants grouped messages into between 2 and 13 separate categories. Similarity analysis showed four groupings of messages, however, some had an agreement below 50% and clusters appeared dispersed. In the second wave, and after messages being edited, participants grouped the messages into between 4 and 9 categories. Five groups (now including positive reinforcement messages) were identified with higher agreement in the similarity and cluster analyses. CONCLUSIONS: The structure of expert-developed text messages to address medication adherence key barriers was confirmed. Messages will be used in future research to determine their impact on affecting medication adherence to anti-hypertensive medications using a reinforcement learning controlled text messaging service.
Authors: Justin Gatwood; Rajesh Balkrishnan; Steven R Erickson; Lawrence C An; John D Piette; Karen B Farris Journal: Res Social Adm Pharm Date: 2014-02-05
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